Structured medication reviews for adults with multimorbidity and polypharmacy in primary care: a systematic review protocol
Bibliographic record
Abstract
INTRODUCTION: Polypharmacy is common among individuals with multimorbidity, often leading to inappropriate medication use and is associated with an increased risk of frailty, hospitalisation and mortality. Structured medication reviews (SMRs) have emerged as a promising method for optimising medication use. However, research examining their efficacy is limited. This review aims to evaluate the impact of SMRs on improving outcomes for adults with multimorbidity and polypharmacy in primary care settings. Additionally, this review seeks to identify prevailing patterns and trends in the mode of delivery of SMRs. METHODS AND ANALYSIS: A systematic review will be conducted using Ovid MEDLINE, Ovid EMBASE, Web of Science and CINAHL (1997-present). Primary outcomes will include medication-related measures such as dose, frequency and dosage form. Secondary outcomes under investigation will include physical, mental, functional and health service outcomes, as reported. Two independent reviewers will conduct the screening and data extraction, resolving disagreements through discussion. Once eligible studies are identified, the extracted data will be summarised in tabular format. The risk of bias in the articles will be assessed using either the Cochrane Risk of Bias 2 tool or the Newcastle-Ottawa scale, depending on the design of the studies retrieved. Subgroup analysis will be performed using demographic variables and modes of delivery where the data supports. If appropriate, a meta-analysis of the data extracted will be conducted to determine the impact of the SMRs on reported outcomes. If a meta-analysis is not possible due to heterogeneity, a narrative synthesis approach will be adopted. ETHICS AND DISSEMINATION: This proposed review is exempt from ethical approval as it aims to collate and summarise peer-reviewed, published evidence. This protocol and the subsequent review will be disseminated in peer-reviewed journals, conferences and patient-led lay summaries. PROSPERO REGISTRATION NUMBER: CRD42023454965.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.077 | 0.075 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.020 | 0.016 |
| Bibliometrics | 0.017 | 0.017 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.068 | 0.011 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".